The principles of immune system function are derivable from a consideration of its evolutionary origins. The rate of germline evolution of pathogens is vastly more rapid than that of their vertebrate hosts. The solution used by evolution was to couple a somatically generated, random recognitive repertoire to the handful of biodestructive mechanisms largely existent in non-vertebrates. This required two new regulatory mechanisms: 1) a somatic decision mechanism to sort the repertoire into anti-self (inactivated) leaving a residue anti- nonself (activated) to protect the host and 2) a germline-selected decision mechanism to control the class and magnitude of the effector response. In order to confront its complexity, the system can be divided into modules, each describable by a theoretical construct. These can then be connected to provide a framework that permits analysis of an in vivo immune response. As the system is multivariate, the computer becomes an essential tool, not only to keep track of all of the data inputs, but to extract any cryptic conclusions amenable to experimental attack. The constructs being developed cover most of immune behavior: the Combinatorial Theory of the nature of the repertoire, the Associative Recognition Theory of the Self-Nonself discrimination, Trauma Theory for the determination of the magnitude and effector class of the response, the B-Protecton Theory of humoral responsiveness and the T- Protecton Theory of cell-mediated responsiveness. These theories will be linked together by a computer program referred to as SIS, the Synthetic Immune System. The success of this approach will be seen in several ways. First, discordance between mechanism and behavior can be revealed. Second, the consequence of a given antigenic input should be predictable. Third, an a priori evaluation of clinical application at the level of the self- nonself discrimination and the regulation of effector class will become possible. Lastly, the most precious result will be the "understanding" that optimally precedes successful manipulation and which is derived from the availability of an integrative and predictive analytical tool. PUBLIC HEALTH RELEVANCE: The complexity of scientific information is making it unavoidable that computer modeling based on sound biological principles be used to manipulate the data in a manner that predicts the outcome of a pathogen - immune system interaction. A comprehensive model will permit optimal design of vaccines, provide protocols to control autoimmunity and immunopathology, allow rational approaches to cancer immunotherapy and suggest manipulations to regulate the causes and course of allergic episodes. The influx of mathematicians and computer modelers is clearly changing the way we analyze immune behavior.